The work deals with design and implementation of the program, which can be used to clarify text retrieval algorithms using a graphical view of their structures. The work includes analyzis of already existing, visualiz...
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The work deals with design and implementation of the program, which can be used to clarify text retrieval algorithms using a graphical view of their structures. The work includes analyzis of already existing, visualization tools designed to address other areas as well.
It is often a challenge to find interesting and appropriate data sets to use as examples to demonstrate graph data structures and algorithms. Goals for the data are often conflicting. The data should include examples ...
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ISBN:
(纸本)9781450310987
It is often a challenge to find interesting and appropriate data sets to use as examples to demonstrate graph data structures and algorithms. Goals for the data are often conflicting. The data should include examples small enough to work through in a class example by hand, but some large enough to demonstrate important behaviors of a structure or algorithm. Data should be freely available in a convenient format and should have some real-world relevance. visualization of the data and results computed from it is helpful. This paper describes a collection of graph data sets generated from the Clinched Highway Mapping Project's highway data and some examples of their use in undergraduate courses on data structures and algorithms. The source data, the process used to convert the data into a more useful format, some examples of its use, and a visualization tool using the Google Maps API, are described.
We report on the state of the field of algorithm visualization, both quantitatively and qualitatively. Computer science educators seem to find algorithm and data structure visualizations attractive for their classroom...
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We report on the state of the field of algorithm visualization, both quantitatively and qualitatively. Computer science educators seem to find algorithm and data structure visualizations attractive for their classrooms. Educational research shows that some are effective while many are not. Clearly, then, visualizations are difficult to create and use right. There is little in the way of a supporting community, and many visualizations are downright poor. Topic distribution is heavily skewed towards simple concepts with advanced topics receiving little to no attention.
We have cataloged nearly 400 visualizations available on the Internet. We have a wiki-based catalog which includes availability, platform, strengths and weaknesses, responsible personnel and institutions, and other data about each visualization. We have developed extraction and analysis tools to gather statistics about the corpus of visualizations.
Based on analysis of this collection, we point out areas where improvements may be realized and suggest techniques for implementing such improvements. We pay particular attention to the free and open source software movement as a model which the visualization community may do well to emulate, from both a software engineering perspective and a community-building standpoint.
The work deals with design and implementation of the program, which is used to clarify the operation of algorithms for searching through text using a graphical view of their structures. The work also includes some ana...
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The work deals with design and implementation of the program, which is used to clarify the operation of algorithms for searching through text using a graphical view of their structures. The work also includes some analyzis of already existing, interesting visualization tools designed to address other areas.
More collaborative use of visualizations is taking place in the classrooms due to the introduction of pair programming and collaborative learning as teaching and learning methods. This introduces new challenges to the...
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ISBN:
(纸本)9781595936103
More collaborative use of visualizations is taking place in the classrooms due to the introduction of pair programming and collaborative learning as teaching and learning methods. This introduces new challenges to the visualization tools, and thus, research and theory to support the development of collaborative visualization tools is needed. We present an empirical study in which the learning outcomes of students were compared when students were learning in collaboration and using materials which contained visualizations on different, engagement levels. Results indicate that the level of engagement has an effect on students learning results although the difference is not statistically significant. Especially students without previous knowledge seem to gain more from using visualizations on higher engagement level.
Pedagogical algorithm visualization (AV) systems produce graphical representations that aim to assist learners in understanding the dynamic behavior of computer algorithms. In order to foster active learning, computer...
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Pedagogical algorithm visualization (AV) systems produce graphical representations that aim to assist learners in understanding the dynamic behavior of computer algorithms. In order to foster active learning, computer science educators have developed AV systems that empower learners to construct their own visualizations of algorithms under study. Notably, these systems support a similar development model in which coding an algorithm is temporally distinct from viewing and interacting with the resulting visualization. Given that they are known to have problems both with formulating syntactically correct code, and with understanding how code executes, novice learners would appear likely to benefit from a more "live" development model that narrows the gap between coding an algorithm and viewing its visualization. In order to explore this possibility, we have implemented "What You See Is What You Code," an algorithm development and visualization model geared toward novices first learning to program under the imperative paradigm. In the model, the line of algorithm code currently being edited is reevaluated on every edit, leading to immediate syntactic feedback, along with immediate semantic feedback in the form of an AV. Analysis of usability and field studies involving introductory computer science students suggests that the immediacy of the model's feedback can help novices to quickly identify and correct programming errors, and ultimately to develop semantically correct code. (C) 2006 Elsevier Ltd. All rights reserved.
We argue that algorithm visualization techniques can be usefully applied to the teaching of NP-completeness results. On the ground of this opinion and of a quite positive preliminary student evaluation, we have thus i...
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ISBN:
(纸本)9781605588209
We argue that algorithm visualization techniques can be usefully applied to the teaching of NP-completeness results. On the ground of this opinion and of a quite positive preliminary student evaluation, we have thus included the visualization of four well-known NP-completeness proofs into the distribution of the AlViE algorithm visualization environment.
Data structures and algorithms are important foundation topics in computer science education. However, they are often complex and hard to understand. As a result, educational tools, such as algorithm visualization sys...
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Data structures and algorithms are important foundation topics in computer science education. However, they are often complex and hard to understand. As a result, educational tools, such as algorithm visualization systems, are always needed to help students better learn and understand algorithms. The focus on graphics and sound instead of pedagogical aspects in the design of current algorithm visualization systems undermines effectiveness in teaching algorithms. In addition, most algorithm visualization systems lack features that encourage student engagement. This research addresses some required issues in creating algorithm visualization techniques by integrating learning theories and models in algorithm learning and by visualizing algorithms using computer games to fully engage students in the algorithm learning process. A new algorithm visualization and learning approach, namely algorithm visualization using Serious Games (AVuSG), has been introduced. It visualizes algorithms using educational or serious games to benefit from their popularity and engagement to motivate students who are learning algorithms. Moreover, it facilitates the students' assessment using the winning-losing criteria of computer games without the need for external questions. The conceptual framework of AVuSG visualizes the algorithm to be learned using three forms of representations: Text, Flowchart, and Computer Game. Moreover, it defines three types of learning processes: Viewing,Playing, and Designing, which learners can use to engage with any of the three forms of the produced algorithm visualizations.@pqdt@break@Finally, AVuSG integrates learning theories with game design to introduce three learning models: Bloom Based, Gagne Based, and Constructivist Models, which can be adopted either by students to learn the algorithm or by the instructors to teach the algorithm depending on the learning objectives that they want to achieve.@pqdt@break@To demonstrate AVuSG framework, a software syste
In this paper, we present a learning support system DASE-E to help students understand fundamental concepts of distributed algorithms in computer science. DASE-E is a collaborative learning system, in which the task o...
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In this paper, we present a learning support system DASE-E to help students understand fundamental concepts of distributed algorithms in computer science. DASE-E is a collaborative learning system, in which the task of students is to devise a distributed algorithm. DASE-E offers a set of small wireless terminals with accelerometers. Each student plays the role of a process with a terminal, according to the algorithm that students devised. Each terminal enables a student to take physical actions that control the behavior of a process in the simulator. After the role playing simulation is finished, students discuss their activity played back on a *** implemented the system for learning distributed leader election algorithms, had a trial exercise in our research group, and we confirmed that it is effective to learn the critical part of distributed systems and algorithms.
This article reviews successful educational experiences in using program and algorithm visualizations (PAVs). First, we survey a total of 18 PAV systems that were subject to 33 evaluations. We found that half of the s...
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This article reviews successful educational experiences in using program and algorithm visualizations (PAVs). First, we survey a total of 18 PAV systems that were subject to 33 evaluations. We found that half of the systems have only been tested for usability, and those were shallow inspections. The rest were evaluated with respect to their educational effectiveness. Script-based systems seem to be well suited for the viewing, responding, and changing engagement levels, while compiler-based systems do well for the construction and presenting engagement levels. Finally, we analyze additional PAV features of successful evaluations and hypothesize that they are relevant.
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